Xingxing Zhang1, Carson Ingo2, Wouter M Teeuwisse1, Zhensen Chen3, Matthias J P van Osch1,4. 1. Department of Radiology, C. J. Gorter Center for High Field MRI, Leiden University Medical Center, Leiden, Netherlands. 2. Department of Physical Therapy and Human Movement Sciences, Northwestern University, Chicago, Illinois, USA. 3. Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China. 4. Leiden Institute for Brain and Cognition, Leiden University, Leiden, Netherlands.
Abstract
PURPOSE: Applications of intravoxel incoherent motion (IVIM) imaging in the brain are scarce, whereas it has been successfully applied in other organs with promising results. To better understand the cerebral IVIM signal, the diffusion properties of the arterial blood flow within different parts of the cerebral vascular tree (i.e., different generations of the branching pattern) were isolated and measured by employing an arterial spin labeling (ASL) preparation module before an IVIM readout. METHODS: ASL preparation was achieved by T1 -adjusted time-encoded pseudo-continuous ASL (te-pCASL). The IVIM readout module was achieved by introducing bipolar gradients immediately after the excitation pulse. The results of ASL-IVIM were compared with those of conventional IVIM to improve our understanding of the signal generation process of IVIM. RESULTS: The pseudo-diffusion coefficient D* as calculated from ASL-IVIM data was found to decrease exponentially for postlabeling delays (PLDs) between 883 ms and 2176 ms, becoming relatively stable for PLDs longer than 2176 ms. The fast compartment of the conventional IVIM-experiment shows comparable apparent diffusion values to the ASL signal with PLDs between 1747 ms and 2176 ms. At the longest PLDs, the observed D* values (4.0 ± 2.8 × 10-3 mm2 /s) are approximately 4.5 times higher than the slow compartment (0.90 ± 0.05 × 10-3 mm2 /s) of the conventional IVIM experiment. CONCLUSION: This study showed much more complicated diffusion properties of vascular signal than the conventionally assumed single D* of the perfusion compartment in the two-compartment model of IVIM (biexponential behavior). Magn Reson Med 79:723-729, 2018.
PURPOSE: Applications of intravoxel incoherent motion (IVIM) imaging in the brain are scarce, whereas it has been successfully applied in other organs with promising results. To better understand the cerebral IVIM signal, the diffusion properties of the arterial blood flow within different parts of the cerebral vascular tree (i.e., different generations of the branching pattern) were isolated and measured by employing an arterial spin labeling (ASL) preparation module before an IVIM readout. METHODS: ASL preparation was achieved by T1 -adjusted time-encoded pseudo-continuous ASL (te-pCASL). The IVIM readout module was achieved by introducing bipolar gradients immediately after the excitation pulse. The results of ASL-IVIM were compared with those of conventional IVIM to improve our understanding of the signal generation process of IVIM. RESULTS: The pseudo-diffusion coefficient D* as calculated from ASL-IVIM data was found to decrease exponentially for postlabeling delays (PLDs) between 883 ms and 2176 ms, becoming relatively stable for PLDs longer than 2176 ms. The fast compartment of the conventional IVIM-experiment shows comparable apparent diffusion values to the ASL signal with PLDs between 1747 ms and 2176 ms. At the longest PLDs, the observed D* values (4.0 ± 2.8 × 10-3 mm2 /s) are approximately 4.5 times higher than the slow compartment (0.90 ± 0.05 × 10-3 mm2 /s) of the conventional IVIM experiment. CONCLUSION: This study showed much more complicated diffusion properties of vascular signal than the conventionally assumed single D* of the perfusion compartment in the two-compartment model of IVIM (biexponential behavior). Magn Reson Med 79:723-729, 2018.
Authors: Zixuan Lin; Yang Li; Pan Su; Deng Mao; Zhiliang Wei; Jay J Pillai; Abhay Moghekar; Matthias van Osch; Yulin Ge; Hanzhang Lu Journal: Magn Reson Med Date: 2018-03-01 Impact factor: 4.668